Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique

This work evaluates the performance of some methods oriented towards the generation of the volume of four subdural hematomas (SDH), present in multi-layer computed tomography images. To do this, firstly, a reference volume is specified: the volume obtained by a neurosurgeon using the manual planimet...

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Autores:
Vera, Miguel
Huérfano, Yoleidy
Borrero, Maryury
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Barrera, Doris
Hernández, Carlos
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar MSc, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/2526
Acceso en línea:
http://hdl.handle.net/20.500.12442/2526
Palabra clave:
ABC Methods
Automatic Intelligent Technique
Segmentation
Volumetry of subdural hematomas
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas subdurales
Rights
License
Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
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dc.title.eng.fl_str_mv Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
dc.title.alternative.spa.fl_str_mv Volumetría de hematomas subdurales en imágenes de tomografía computarizada: métodos abc versus una técnica computacional inteligente
title Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
spellingShingle Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
ABC Methods
Automatic Intelligent Technique
Segmentation
Volumetry of subdural hematomas
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas subdurales
title_short Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
title_full Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
title_fullStr Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
title_full_unstemmed Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
title_sort Volumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational technique
dc.creator.fl_str_mv Vera, Miguel
Huérfano, Yoleidy
Borrero, Maryury
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Barrera, Doris
Hernández, Carlos
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar MSc, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
dc.contributor.author.none.fl_str_mv Vera, Miguel
Huérfano, Yoleidy
Borrero, Maryury
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Barrera, Doris
Hernández, Carlos
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar MSc, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
dc.subject.eng.fl_str_mv ABC Methods
Automatic Intelligent Technique
Segmentation
Volumetry of subdural hematomas
topic ABC Methods
Automatic Intelligent Technique
Segmentation
Volumetry of subdural hematomas
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas subdurales
dc.subject.spa.fl_str_mv Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas subdurales
description This work evaluates the performance of some methods oriented towards the generation of the volume of four subdural hematomas (SDH), present in multi-layer computed tomography images. To do this, firstly, a reference volume is specified: the volume obtained by a neurosurgeon using the manual planimetric method (MPM); which allows the generation of manual segmentations of space-occupying lesions. In this case, these volumes are matched with the SDH. In parallel, the volumetry of the 4 SDHs is obtained, considering both the original version of the ABC/2 method and two of its variants, identified in this paper as ABC/3 method and 2ABC/3 method. The ABC methods allow the calculation of the volume of the hematoma under the assumption that the SDH has an ellipsoidal shape. In third place, SDH’s are studied through an intelligent automatic technique (SAT) that generates the three-dimensional segmentation of each SDH. Finally, the percentage relative error is calculated as a metric to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance generating an average percentage error of less than 5%.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2019-01-25T15:54:41Z
dc.date.available.none.fl_str_mv 2019-01-25T15:54:41Z
dc.type.eng.fl_str_mv article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.identifier.issn.none.fl_str_mv 26107988
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12442/2526
identifier_str_mv 26107988
url http://hdl.handle.net/20.500.12442/2526
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
rights_invalid_str_mv Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
http://purl.org/coar/access_right/c_abf2
dc.publisher.spa.fl_str_mv Sociedad Venezolana de Farmacología Clínica y Terapéutica
dc.source.spa.fl_str_mv Revista AVFT-Archivos Venezolanos de Farmacología y Terapéutica
Vol. 37, No. 4 (2018)
institution Universidad Simón Bolívar
dc.source.uri.eng.fl_str_mv http://www.revistaavft.com/images/revistas/2018/avft_4_2018/3_volumetryof_subdoral.pdf
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spelling Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Vera, Miguelc485e4e3-5bbd-4d00-8ec7-e5bc8a0a21e3Huérfano, Yoleidy769899ba-e6a1-4144-95c2-ff4614f93578Borrero, Maryuryce8424b3-6f43-4a46-8f73-214fafbb62fdValbuena, Oscar262b3f8e-b422-4786-b036-2aaa5b963f84Salazar, Williamsfd007214-08c4-4cd6-ae19-7f2ba4f184eaVera, María Isabelc522f56e-ec03-4aa6-9e83-d339a37388acBarrera, Doris4b365c16-7d6f-4aee-985c-e70d635e8807Hernández, Carlosa82d5fb1-0724-456f-8223-93882ad7278dMolina, Ángel Valentín5fcd607f-8710-40a9-b4dc-b9d1f71d1c1eMartínez, Luis Javierd0fa0a36-7752-496a-979e-48fdb02a5ee9Salazar MSc, Juan11555c88-5042-49af-a84b-f8da60181445Gelvez, Elkin90dd023c-1cb7-48ef-bff5-4071ee82a94cContreras, Yudith5ec79ce9-bc7e-44bb-95cb-bf1dab3e3a64Sáenz, Frank5a93b50c-3ebe-476e-8aa6-4286185e2b1d2019-01-25T15:54:41Z2019-01-25T15:54:41Z201826107988http://hdl.handle.net/20.500.12442/2526This work evaluates the performance of some methods oriented towards the generation of the volume of four subdural hematomas (SDH), present in multi-layer computed tomography images. To do this, firstly, a reference volume is specified: the volume obtained by a neurosurgeon using the manual planimetric method (MPM); which allows the generation of manual segmentations of space-occupying lesions. In this case, these volumes are matched with the SDH. In parallel, the volumetry of the 4 SDHs is obtained, considering both the original version of the ABC/2 method and two of its variants, identified in this paper as ABC/3 method and 2ABC/3 method. The ABC methods allow the calculation of the volume of the hematoma under the assumption that the SDH has an ellipsoidal shape. In third place, SDH’s are studied through an intelligent automatic technique (SAT) that generates the three-dimensional segmentation of each SDH. Finally, the percentage relative error is calculated as a metric to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance generating an average percentage error of less than 5%.Este trabajo evalúa el rendimiento de algunos métodos orientados a la generación del volumen de cuatro hematomas subdurales (SDH), presentes en imágenes de tomografía computarizada multicapa. Para hacer esto, en primer lugar, se especifica un volumen de referencia: el volumen obtenido por un neurocirujano utilizando el método planimétrico manual (MPM); que permite la generación de segmentaciones manuales de lesiones ocupantes de espacio. En este caso, estos volúmenes se comparan con el SDH. Paralelamente, se obtiene la volumetría de los 4 SDH, considerando tanto la versión original del método ABC / 2 como dos de sus variantes, identificadas en este documento como el método ABC / 3 y el método 2ABC / 3. Los métodos ABC permiten el cálculo del volumen del hematoma bajo el supuesto de que el SDH tiene una forma elipsoidal. En tercer lugar, los SDH se estudian a través de una técnica automática inteligente (SAT) que genera la segmentación tridimensional de cada SDH. Finalmente, el error relativo porcentual se calcula como una métrica para evaluar las metodologías consideradas. Los resultados muestran que el método SAT exhibe el mejor rendimiento generando un porcentaje de error promedio de menos del 5%.engSociedad Venezolana de Farmacología Clínica y TerapéuticaRevista AVFT-Archivos Venezolanos de Farmacología y TerapéuticaVol. 37, No. 4 (2018)http://www.revistaavft.com/images/revistas/2018/avft_4_2018/3_volumetryof_subdoral.pdfABC MethodsAutomatic Intelligent TechniqueSegmentationVolumetry of subdural hematomasMétodos ABCTécnica automática inteligenteSegmentaciónVolumetría de hematomas subduralesVolumetry of subdural hematomas in computed tomography images: ABC methods versus an intelligent computational techniqueVolumetría de hematomas subdurales en imágenes de tomografía computarizada: métodos abc versus una técnica computacional inteligentearticlehttp://purl.org/coar/resource_type/c_6501Stippler M. Craniocerebral trauma. In: Daroff RB, Jankovic J, Mazziotta JC, Pomeroy SL, eds. Bradley’s Neurology in Clinical Practice. 7th ed. Philadelphia, PA: Elsevier; 2016:chap 62.Stanišić M., Hald J., Groote I., Pripp A., Ivanović J., Kolstad F., Sundseth J., Züchner M., Lindegaard K. (2013). Volume and densities of chronic subdural haematoma obtained from CT imaging as predictors of postoperative recurrence: a prospective study of 107 operated patients. Acta Neurochir (Wien) 2013 Feb; 155(2): 323–333.Stanišić M., Groote I., Hald J., Pripp A. (2014). Estimation of Chronic Subdural Hematoma Size Using CT Imaging: A Comparison of In- Plane Thickness to 3D Volumetry. Open Journal of Modern Neurosurgery, 2014, 4, 1-6.Wang Y., Li Y., Zhu Y., Lin T., Zhang Y., Huaizhang Shi Y. (2017). A novel and precise method for evaluation of chronic subdural hematoma volume. Int J Clin Exp Med 2017;10(4):6198-6203.Maiera A, Wigstrm L, Hofmann H, Hornegger J, Zhu L, Strobel N, Fahrig R. Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT. Medical Physics. 2011;38(11):5896–909.Kroft L, De Roos A, Geleijns J. Artifacts in ECG–synchronized MDCT coronary angiography. American Journal of Roentgenology. 2007;189(3):581–91.Sucu H., Gokmen M., Gelal F. The value of XYZ/2 technique compared with computer-assisted volumetric analysis to estimate the volume of chronic subdural hematoma. Stroke 2005; 36: 998-1000.Freeman, W., Barrett, K., Bestic, J.,Meschia, J., Broderick, D., Brott, T. Computer-assisted volumetric analysis compared with ABC/2 method for assessing warfarinrelated intracranial hemorrhage volumes. 2008, Neurocritical Care, 9, 307–312.Kamnitsas K., Lediga C., Newcombeb V., Simpsonb J., Kaneb A., Menonb D., Rueckerta D., Glockera B. Efficient Multi-Scale 3D CNN with fully connected CRF for Accurate Brain Lesion Segmentation. Medical Image Analysis, Vol 23, pp.1603-1659, 2017.Prakash K., Zhou S., Morgan T., Hanley D., Nowinski W. Segmentation and quantification of intra-ventricular/cerebral hemorrhage in CT scans by modified distance regularized level set evolution technique. Int J Comput Assist Radiol Surg. 2012; 7(5): 785-798.Huttner H., Steiner T., Hartmann M., Köhrmann M., Juettler E., Mueller S, Wikner J., Meyding U., Schramm P., Schwab S. y Schellinger P. (2006). Comparison of ABC/2 Estimation Technique to Computer- Assisted Planimetric Analysis in Warfarin-Related Intracerebral Parenchymal Hemorrhage. Stroke. 2006;37:404-408.Mezzadri J., Goland J., y Sokolvsky M. Introducción a la Neurocirugía. Capítulo: Patología vascular II. Ediciones Journal. Segunda edición. 2011.Vera M. Segmentación de estructuras cardiacas en imágenes de tomografía computarizada multi-corte. Ph.D. dissertation, Universidad de los Andes, Mérida-Venezuela, 2014.Vera M., Huérfano Y., Contreras J., Vera M. I., Salazar W., Vargas S., Chacón J. y Rodríguez J. (2017). Desarrollo de una Técnica Computacional No Lineal para la Segmentación de Hematomas Subdurales, presentes en Imágenes de Tomografía Computarizada Cerebral. AVFT Archivos Venezolanos de Farmacología y Terapéutica. 36(6), 168-173ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf700063https://bonga.unisimon.edu.co/bitstreams/a2137dab-ee90-4ae5-9a70-866769b45226/download382a461247716f4d6260f13cab55b782MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-8368https://bonga.unisimon.edu.co/bitstreams/b22d7bb2-d6b7-436f-8e63-d89921b9470e/download3fdc7b41651299350522650338f5754dMD52TEXTVolumetry of subdural hematomas.pdf.txtVolumetry of subdural hematomas.pdf.txtExtracted texttext/plain24045https://bonga.unisimon.edu.co/bitstreams/8eef6427-36d0-4d55-b255-7c3ba1a000b8/downloadf485b79864766b5a5098517c0816e111MD53PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain24411https://bonga.unisimon.edu.co/bitstreams/bacc2166-d26e-4592-ae55-59ae267247cf/downloada3ceb06abb461e41f0454d7066ce3c63MD55THUMBNAILVolumetry of subdural hematomas.pdf.jpgVolumetry of subdural hematomas.pdf.jpgGenerated Thumbnailimage/jpeg1892https://bonga.unisimon.edu.co/bitstreams/57aefc67-432e-43bd-879f-cb17607eacd2/downloadc3ecd045d9f1cf14b6998648ba60f22dMD54PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg6227https://bonga.unisimon.edu.co/bitstreams/f141a12b-64c3-48b9-91fc-8a82b323e7a5/downloade8aa48bdbea9e6243aadb776694f5a53MD5620.500.12442/2526oai:bonga.unisimon.edu.co:20.500.12442/25262024-08-14 21:53:19.088open.accesshttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.coPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj48aW1nIGFsdD0iTGljZW5jaWEgQ3JlYXRpdmUgQ29tbW9ucyIgc3R5bGU9ImJvcmRlci13aWR0aDowIiBzcmM9Imh0dHBzOi8vaS5jcmVhdGl2ZWNvbW1vbnMub3JnL2wvYnktbmMvNC4wLzg4eDMxLnBuZyIgLz48L2E+PGJyLz5Fc3RhIG9icmEgZXN0w6EgYmFqbyB1bmEgPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj5MaWNlbmNpYSBDcmVhdGl2ZSBDb21tb25zIEF0cmlidWNpw7NuLU5vQ29tZXJjaWFsIDQuMCBJbnRlcm5hY2lvbmFsPC9hPi4=

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